Bibliographic record
Abstract
The study indicates that classroom observation is potentially a useful tool for teachers’ professional development and works best when the personal capacity of a teacher, an observer, and school provide a base for the effective use and outcome for teachers.A brief summary of major findings and lessons learnt from the project, process, learning of teachers and my own learning is presented as follows;i) Teachers found the pre and post-observation sessions very useful for their professional development. These sessions also help the observer to understand the roots of the teacher's classroom problems.ii) Cyclical observations provide the courage and intellectual capacity to the teachers to turn their focus upon improved actions and they also developed their professional skills.iii) Teachers perceived my role as a helper, facilitator and a resource person who could provide suggestions and alternatives, where needed. I feel the need to further explore, how reflective conversations between a teacher and an observer affect individual teacher's attitudes and behaviour. This will highlight what needs to be done further to improve individual competencies. However, I feel that a co-teaching experience can also provide a valuable basis for collaborative inquiry. It might raise a range of interesting issues and questions for using reflective conversation in planning, teaching, and improving this strategy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".